These components join Yarn, MapReduce and HDFS from ODPi Runtime Specification 1.0. By including Apache Hive, which read, write, and manage large datasets residing in distributed storage, ODPi will reduce SQL query inconsistencies across Hadoop Platforms.

ODPi will base its work on Hive version 1.2 and ensure there is core functionality that will continue to behave in a standard way for future versions of Apache Hive.

HCFS support will enable storage and cloud vendors to leverage ODPi standards, letting them leverage their native storage solutions as part of an ODPi Runtime Compliant Hadoop Platform and reduce the incompatibilities that end-users face.

“As our work continues to complement the Apache Software Foundation, ODPi is helping the Hadoop ecosystem become more valuable to those who are testing and building big data applications,” said John Mertic, director of ODPi. “Through a common specification, we are enabling developers to easily write applications that sit on top of big data stacks, lowering the costs of interoperability across systems. For enterprises, the benefits are increased efficiency, flexibility and smoother maintenance.”